文献类型：期刊文献

英文题名：A convex programming approach for ridesharing user equilibrium under fixed driver/rider demand

作者：Wang, Xiaolei[1];Wang, Jun[2];Guo, Lei[3];Liu, Wei[4,5];Zhang, Xiaoning[1]

机构：[1]Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China;[2]Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong, Peoples R China;[3]East China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[4]Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW 2052, Australia;[5]Univ New South Wales, Sch Civil & Environm Engn, Res Ctr Integrated Transport Innovat, Sydney, NSW 2052, Australia

年份：2021

卷号：149

起止页码：33

外文期刊名：TRANSPORTATION RESEARCH PART B-METHODOLOGICAL

收录：;EI(收录号：20212410501539);WOS:【SSCI(收录号:WOS:000664741600003)，SCI-EXPANDED(收录号:WOS:000664741600003)】；

基金：We wish to express our sincere thanks to the two enthusiastic anonymous reviewers who offer thorough and constructive comments to help us improve the exposition of the paper. The work described in this study was supported by grants from the National Natural Science Foundation of China under Project No. 72022013 , No. 71974146 , No. 11771287 , No. 72021002 , No. 71890973 . Dr. Wei Liu thanks the funding support from the Australian Research Council (DE200101793) . The views expressed herein are those of the authors and are not necessarily those of the institute.

语种：英文

外文关键词：Traffic assignment; Ridesharing; User equilibrium; Network

摘要：With the proliferation of smartphone-based ridesharing apps around the world, traffic assignment with ridesharing is drawing increasing attention in recent years. A number of ridesharing user equilibrium (RUE) models have been proposed, but most of them are formulated as path-based mixed complementarity problems based on presumed ridesharing price and inconvenience functions, thus are inconvenient to implement in reality. In this study, by redefining the set of feasible driver trajectories and the market equilibrium conditions for ridesharing, we propose an alternative approach to modeling the RUE when the driver- and rider-demand for each OD pair are fixed and given. We show that the resulting RUE conditions can be equivalently transformed into a convex programming problem, and the existence and uniqueness of RUE link flows are guaranteed under mild conditions. The structure of the model is similar to the classic Beckmann's formulation, except for the additional ridesharing demand-supply constraints. So a dual subgradient algorithm with averaging is proposed to solve the problem, and the dual sub-problem can be solved by the Frank-Wolfe method. The algorithm effectively avoids path enumeration, therefore is implementable on large networks. The impact of problem size on the computational efficiency of the algorithm is theoretically analyzed and numerically demonstrated. (C) 2021 Elsevier Ltd. All rights reserved.